Triple
T12592613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ōta |
E300642
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Magome |
E949039
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Magome | Statement: [Ōta, hasPart, Magome]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Magome Context triple: [Ōta, hasPart, Magome]
-
A.
Magome
chosen
Magome is a residential neighborhood in Tokyo known for its quiet streets and historical association with writers and literary figures.
-
B.
Kamitsumaki
Kamitsumaki is the first volume of the ancient Japanese chronicle Kojiki, focusing on Shinto creation myths and the age of the gods.
-
C.
Zaimu-shō
Zaimu-shō is Japan’s Ministry of Finance, the central government body responsible for national fiscal policy, budgeting, taxation, and public finance management.
-
D.
Marunouchi
Marunouchi is a central Tokyo business district known for its concentration of corporate headquarters, upscale offices, and proximity to Tokyo Station and the Imperial Palace.
-
E.
Takamikura
Takamikura is the ornate imperial throne used in Kyoto for the enthronement ceremonies of Japanese emperors.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d7bde87b648190bcd0266e9efde098 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954cc6d3c81908fbb22601c46f3f7 |
completed | April 10, 2026, 7:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f69b847de481908163d59cc939e132 |
completed | May 3, 2026, 12:49 a.m. |
Created at: April 9, 2026, 5:07 p.m.